As shown in Fig. REF , our per-point classification network consists of four parts: point cloud encoder, point cloud decoder, image encoder and image-point cloud attention fusion. The point cloud encoder/decoder follows the design of SO-Net [1]} and PointNet++ [2]}, while the image encoder is a ResNet-34 [3]}.
The classified points are then used in our inverse camera projection optimization in Section REF  to solve for the unknown camera pose.
<FIGURE>